Abstract

Approximate message passing (AMP) is an iterative signal recovery algorithm for compressed sensing (CS) applications. In this letter, we present an integral-based orthogonal AMP (IB-OAMP) technique that avoids the requirements of AMP (and also the original form of OAMP) on differentiable and separable denoisers. The orthogonality in IB-OAMP can be established using a Monte Carlo method similar to the training stage in a machine-learning algorithm. These features make IB-OAMP attractive to be used in conjunction with some well-studied denoising algorithms.

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